Results of the iSEGMound Workflow

In this Master’s thesis two data preparation methods (DTm and Multi-Scale Topographic Index) and two segmentation methods (Watershed and Region Growing) were used and compared. The four workflows were tested on the Train DTM and the Train Area to understand the relationship between the size of the area of investigation and the variable settings of the respective algorithms. The most effective workflow was chosen to be applied to the five Areas of Interests: AoI 1, AoI 2, AoI 3, AoI 4 and AoI 5.

First let’s have glimpse on the morphometric derivative chosen, the Multi-Scale Topographic Index, on the example of the Train DTM:

Multi-Scale Topographic Index of the Train DTM.

As a reminder let’s see where the burial mound groups Site ID 5 (black) and Site ID 35 (blue) are located in the Training DTM:

Multi-Scale Topographic Index of the Train DTM with bruial mound groups Site ID 5 and 35.

We know from Dobiat et al. 1994, that Site ID 35 was identified as two mounds. As in Chapter 4 discussed, the mounds visible in Figure 68 were possible to be identified on ground.

5.1 Results of the Training DTM

The workflows applied on the Training DTM are the following: 5a_iSEG05_WS, 5b_iSEG05_mtpi_WS, 5c_iSEG05_RG, and 5d_iSEG05_mtpi_RG.

Let’s plot the results of the Training DTM by segmentation. First the Watershed Segmentation based on a DTM (orange segments) and on the SAGA MSTPI:

Plotting iSEG_WS (orange) and iSEG_mtpi_WS (lilac) on the SAGA MSTPI.

Now, the REgion Growing Segmentation based on a DTM (light blue) and on the SAGA MSTPI:

Plotting iSEG_RG (light blue) and iSEG_mtpi_RG (brown) on the SAGA MSTPI.

From the first results it is clearly visible, that using

5.2 Results of the Training Area The workflows applied on the Training DTM are the following:

6a_iSEG05_WS_ta 6b_iSEG05_mtpi_WS_ta 6c_iSEG05_RG_ta 6d_iSEG05_mtpi_RG_ta

5.3 Choosing the right segmentation

To choose the best working workflow for the Training Area the question posed was: Which segmentation is better? Two different considerations were investigated: the archaeological decision and the statistical decision. From the archaeological point of view the aim is to detect the all (locations of) burial mounds. This can be of course broken down to the question do we want to find the exact shape of the mounds (in the case of the Training DTM and Training Area) or the most important is to detect as much as possible in any shape (e.g. just half or ¾ of a mound is detected) but to detect as as possible of them.